In this paper, two probabilistic adaptive algorithms
for jointly detecting active users in a DS-CDMA system are
reported. The first one, which is based on the theory of hidden
Markov models (HMM’s) and the Baum–Wech (BW) algorithm,
is proposed within the CDMA scenario and compared with
the second one, which is a previously developed Viterbi-based
algorithm. Both techniques are completely blind in the sense that
no knowledge of the signatures, channel state information, or
training sequences is required for any user. Once convergence
has been achieved, an estimate of the signature of each user
convolved with its physical channel response (CR) and estimated
data sequences are provided. This CR estimate can be used to
switch to any decision-directed (DD) adaptation scheme. Performance
of the algorithms is verified via simulations as well as on
experimental data obtained in an underwater acoustics (UWA)
environment. In both cases, performance is found to be highly
satisfactory, showing the near–far resistance of the analyzed algorithms.